Abstract. In this paper, we present a modelling experiment developed to study systems of cities and processes of urbanisation in large territories over long time spans. Building on geographical theories of urban evolution, we rely on agent-based models to 1) formalise complementary and alternative hypotheses of urbanisation and 2) explore their ability to simulate observed patterns in a virtual laboratory. The paper is therefore divided into two sections : an overview of the mechanisms implemented to represent competing hypotheses used to simulate urban evolution; and an evaluation of the resulting model structures in their ability to simulate—efficiently and parsimoniously—a system of cities (between 1000 and 2000 cities in the Former Soviet Union) over several periods of time (before and after the crash of the USSR). We do so using a modular framework of model-building and evolutionary algorithms for the calibration of several model structures. This project aims at tackling equifinality in systems dynamics by confronting different mechanisms with similar evaluation criteria. It enables the identification of the best-performing models with respect to the chosen criteria by scanning automatically the parameter space along with the space of model structures (the different combinations of mechanisms).

Abstract. This paper presents an incremental method of parsimonious modelling using intensive and quantitative evaluation. It is applied to a research question in urban geography, namely how well a simple and generic model of a system of cities can reproduce the evolution of Soviet urbanisation. We compared the ability of two models with different levels of complexity to satisfy goals at two levels. The macro-goal is to simulate the evolution of the system’s hierarchical structure. The micro-goal is to simulate its micro-dynamics in a realistic way. The evaluation of the models is based on empirical data through a calibration that includes sensitivity analysis using genetic algorithms and distributed computing. We show that a simple model of spatial interactions cannot fully reproduce the observed evolution of Soviet urbanisation from 1959 to 1989. A better fit was achieved when the model’s structure was complexified with two mechanisms. Our evaluation goals were assessed through intensive sensitivity analysis. The complexified model allowed us to simulate the evolution of the Soviet urban hierarchy.

Abstract. Models of social systems generally contain free parameters that cannot be evaluated directly from data. A calibration phase is therefore necessary to assess the capacity of the model to produce the expected dynamics. However, despite the high computational cost of this calibration it doesn’t produce a global picture of the relationship between the parameter space and the behaviour space of the model. The Calibration Profile (CP) algorithm is an innovative method extending the concept of automated calibration processes. It computes a profile that depicts the effect of each single parameter on the model behaviour, independently from the others. A 2-dimensional graph is thus produced exposing the impact of the parameter under study on the capacity of the model to produce expected dynamics. The first part of this paper is devoted to the formal description of the CP algorithm. In the second part,we apply it to an agent based geographical model (SimpopLocal). The analysis of the results brings to light novel insights on the model.

A strong regularity in urban systems has long been identified : the hierarchical distribution of city sizes. Moreover, a closer observation of the evolution of this distribution shows that in the majority of city systems, there is a trend towards a more and more unequal distribution of city sizes. Why does the majority of urban systems show those strong regularities? What are the common growth processes involved? Several dynamic growth models have been proposed but no consensus has yet been reached because of the under-determination of models by those empirical laws. In this presentation we describe a new method of agent-based parsimonious modeling that we think can contribute to the identification of the common urban growth processes. This modeling method is based on intensive model exploration for quantitative evaluation of implemented mechanisms. The exploration tools were first developed for the evaluation of SimpopLocal, a model of the organization of urban systems when cities first emerged. The use of those exploration tools was then generalized into a modeling method that was applied for the first time with the construction of the MARIUS family of models which aims at reproducing the evolution of Soviet urbanisation between 1959 and 1989. Those two examples show how this new modeling method can help the construction of urban theories by helping the evaluation of assumptions made on urban processes.

In the context of GeoDiverCity, generic properties of city systems are looked for as stylized facts that apply to these particular objects over the world and over time. Examples of those properties lay in the hierarchy of city sizes (expressed by Zipf’s law), or the process of urban growth (as described by Gibrat in 1931). Using those regular patterns, modeling of the co-evolution of cities becomes possible and useful.

Russian cities oppose several obstacles to the observation of such regularities. The spatial limits of the system varies over time, which complicates the choice of urban definition, and the collection of reliable data. Moreover, the historical object of Russia and the Soviet Union exhibits strong specificities related to its (supposed absolute) control over urban definition, development, interactions and inner organization. Our work aims at distinguishing the specific from the generic behavior of the Russian system of cities from the urban transition up to now, in order to model its evolution and propose possible projections with the help of Multi-Agent Models.

This project 1 begins with the harmonization of urban definitions. Theoretical and data collection constraints led us to consider agglomerations of 10.000 inhabitants and more between 1840 and 2010. Agglomerations have been composed of administrative units which take part in the same built-up area in 2010. Since the boundary of the system is not obvious over the XIX and XXth centuries, its larger extension (the Former Soviet Union) is tested along with its present configuration (the Russian Federation).

Generic models (Zipf, Gibrat) are tested and compared with the results obtained in other geographical contexts. Europe, North America, South Africa, India, China and Brazil are represented in the research fields of GeoDiverCity, sharing the same principles of data harmonization, which helps us in the process of comparison. Other tools are used to explore and explain the specificities of the system of Russian cities (analysis of urban trajectories and financial links between cities with the ORBIS Database produced by Bureau van Dijk, 2010 and augmented by C. Rozenblat).

The characteristics of the Russian system learned from these studies, coupled with the experience accumulated within Géographie-Cités and GeoDiverCity will help modeling the system and simulating its possible futures.

Clémentine Cottineau

Notes:

PhD project of Clémentine Cottineau, under the supervision of Denise Pumain (founded by University Paris 1 Panthéon-Sorbonne) ↩

The aim of this series of models 1 is to study growth regimes of systems of cities, which are defined by the nature of the interaction between the cities. Three different stages of urbanisation are considered as resource accessibility, which plays a major role in growth dynamics, takes different forms. For each stage, a set of stylized facts characterizing the state of the system and urban growth dynamics is proposed and defines the structure of an ABM model.

The SimpopLocal model tries to characterise a stylised dynamics of urban emergence. This first urban regime is defined by the role of local environmental constraints on growth. Central to this model is the notion of landscape carrying capacity. Settlement sizes and their growth are controlled by the amount of resources locally available. But innovations and their diffusion in the system thanks to interactions between settlements help to overcome those limitations, eventually producing the proto-structure of urban systems.

The SimpopNet model characterise the progressive networking of urban economies. Innovations in communication and transport networks allow the trade and long distance diffusion of goods and techniques which enables cities to overcome, by importing what was lacking, the local constraints and climatic hazards that limited their growth. In this regime, the resource accessibility of each city is defined by its situation in the network. The SimpopNet model simulates the co-evolution of urban systems and transportation networks.

The SimpopClim model will represent a dynamic regime that takes into account the impact of global environmental constraints on urban dynamics.

This PhD is made possible thanks to interdisciplinary work with computer researchers participating in the GeoDiverCity programme, hired after previous collaboration with ISC-PIF (Romain Reuillon and Mathieu Leclaire, http://www.iscpif.fr/) and a PhD in geomatics conducted by Sébastien Rey Coyrehourcq. The SimpopLocal and SimpopNet models are used as case studies for the development of grid exploration procedures and protocols with OpenMole (http://www.openmole.org/). Those explorations and validating tools are designed to meet the validation and reproducibility requirements and to be generic and adapted to the exploration of spatial simulation models.

Clara Schmitt

Notes:

PhD project of Clara Schmitt, under the supervision of Denise Pumain (founded by ADEME, The French Agency for Environment and Energy) ↩

On Tuesday April 24th 2012, the ERC programs MECHANICITY and GEODIVERCITY met at a pre-AGILE workshop in Avignon.

First part: joint session with Workshop “Complexity modelling for urban structure and dynamics” organised by Bin Jiang and Itzhak Benenson

Mike Batty and Robin Morphet, “Spatial complexity”

Denise Pumain, “Organizing a variety of agent-based models for solving theoretical problems”Itzhak Benenson, “Equations or geosimulation? To understand the phenomenon you need both!”Bin Jiang, “Head/tail breaks: A new classification scheme for data with a heavy-tailed distribution”

Second part: MECHANICITY and GEODIVERCITY

Urban Growth, Chair: Denise Pumain

Elsa Arcaute (MECHANICITY), “Looking for scaling in UK Cities”

Clémentine Cottineau (GEODIVERCITY), “A tool for assessing the specificity of the evolutionary path of Russian cities”

What is GeoDiverCity?

Cities are becoming the habitat of more and more people in the world. All cities are connected by a multitude of networks that make their evolutions becoming more and more interdependent. Our aim is to provide medium-term forecasts of the way in which the urban systems of different continents will evolve, and to explore scenarios whereby these city systems might adapt to the global changes they contribute to shape.
This research programme sets out to gather the main stylised facts making up our knowledge about the dynamics of complex urban systems that has been acquired from observation and different analytical modelling processes, and to use them in new simulation models so as to reconstruct the interaction networks making up these systems. These models will be validated using a multi-scale procedure based on temporal geo-referenced data bases and a new interactive simulation platform.